Tiam1 methylation by NSD2 promotes Rac1 signaling activation and colon cancer metastasis.

Metastasis is a major cause of cancer therapy failure and mortality. However, targeting metastatic seeding and colonization remains a significant challenge. In this study, we identified NSD2, a histone methyltransferase responsible for dimethylating histone 3 at lysine 36, as being overexpressed in metastatic tumors. Our findings suggest that NSD2 overexpression enhances tumor metastasis both in vitro and in vivo. Further analysis revealed that NSD2 promotes tumor metastasis by activating Rac1 signaling. Mechanistically, NSD2 combines with and activates Tiam1 (T lymphoma invasion and metastasis 1) and promotes Rac1 signaling by methylating Tiam1 at K724. In vivo and in vitro studies revealed that Tiam1 K724 methylation could be a predictive factor for cancer prognosis and a potential target for metastasis inhibition. Furthermore, we have developed inhibitory peptide which was proved to inhibit tumor metastasis through blocking the interaction between NSD2 and Tiam1. Our results demonstrate that NSD2-methylated Tiam1 promotes Rac1 signaling and cancer metastasis. These results provide insights into the inhibition of tumor metastasis.

Wafer-Scale Atomic Assembly for 2D Multinary Transition Metal Dichalcogenides for Visible and NIR Photodetection.

The tunable properties of 2D transition-metal dichalcogenide (TMDs) materials are extensively investigated for high-performance and wavelength-tunable optoelectronic applications. However, the precise modification of large-scale systems for practical optoelectronic applications remains a challenge. In this study, a wafer-scale atomic assembly process to produce 2D multinary (binary, ternary, and quaternary) TMDs for broadband photodetection is demonstrated. The large-area growth of homogeneous MoS2, Ni0.06Mo0.26S0.68, and Ni0.1Mo0.9S1.79Se0.21 is carried out using a succinct coating of the single-source precursor and subsequent thermal decomposition combined with thermal evaporation of the chalcogen powder. The optoelectrical properties of the multinary TMDs are dependent on the combination of heteroatoms. The maximum photoresponsivity of the MoS2-, Ni0.06Mo0.26S0.68-, and Ni0.1Mo0.9S1.79Se0.21-based photodetectors is 3.51 × 10-4, 1.48, and 0.9 A W-1 for 532 nm and 0.063, 0.42, and 1.4 A W-1 for 1064 nm, respectively. The devices exhibited excellent photoelectrical properties, which is highly beneficial for visible and near-infrared (NIR) photodetection.

Short tandem repeat expansions in cortical layer-specific genes implicate in phenotypic severity and adaptability of autism spectrum disorder.

AIM: Short tandem repeats (STRs) are repetitive DNA sequences and highly mutable in various human disorders. While the involvement of STRs in various genetic disorders has been extensively studied, their role in autism spectrum disorder (ASD) remains largely unexplored. In this study, we aimed to investigate genetic association of STR expansions with ASD using whole genome sequencing (WGS) and identify risk loci associated with ASD phenotypes. METHODS: We analyzed WGS data of 634 ASD families and performed genome-wide evaluation for 12,929 STR loci. We found rare STR expansions that exceeded normal repeat lengths in autism cases compared to unaffected controls. By integrating single cell RNA and ATAC sequencing datasets of human postmortem brains, we prioritized STR loci in genes specifically expressed in cortical development stages. A deep learning method was used to predict functionality of ASD-associated STR loci. RESULTS: In ASD cases, rare STR expansions predominantly occurred in early cortical layer-specific genes involved in neurodevelopment, highlighting the cellular specificity of STR-associated genes in ASD risk. Leveraging deep learning prediction models, we demonstrated that these STR expansions disrupted the regulatory activity of enhancers and promoters, suggesting a potential mechanism through which they contribute to ASD pathogenesis. We found that individuals with ASD-associated STR expansions exhibited more severe ASD phenotypes and diminished adaptability compared to non-carriers. CONCLUSION: Short tandem repeat expansions in cortical layer-specific genes are associated with ASD and could potentially be a risk genetic factor for ASD. Our study is the first to show evidence of STR expansion associated with ASD in an under-investigated population.

Ruscogenin Exerts Anxiolytic-Like Effect via Microglial NF-κB/MAPKs/NLRP3 Signaling Pathways in Mouse Model of Chronic Inflammatory Pain.

Long-term inflammation can cause chronic pain and trigger patients' anxiety by sensitizing the central nervous system. However, effective drugs with few side effects for treating chronic pain-induced anxiety are still lacking. The anxiolytic and anti-inflammatory effects of ruscogenin (RUS), an important active compound in Ophiopogon japonicus, were evaluated in a mouse model of chronic inflammatory pain and N9 cells. RUS (5, 10, or 20 mg/kg/day, i.g.) was administered once daily for 7 days after CFA injection; pain- and anxiety-like behaviors were assessed in mice. Anti-inflammatory effect of RUS (0.1, 1, 10 µM) on N9 microglia after LPS treatment was evaluated. Inflammatory markers (TNF-α, IL-1ß, IL-6, CD86, IL-4, ARG-1, and CD206) were measured using qPCR. The levels of IBA1, ROS, NF-κB, TLR4, P-IKK, P-IκBα, and P65, MAPKs (ERK, JNK, and P38), NLRP3 (caspase-1, ASC, and NLRP3) were detected by Western blotting or immunofluorescence staining. The potential target of RUS was validated by molecular docking and adeno-associated virus injection. Mice in CFA group exhibited allodynia and anxiety-like behaviors. LPS induced neuroinflammation in N9 cells. Both CFA and LPS increased the levels of IBA1, ROS, and inflammatory markers. RUS (10 mg/kg in vivo and 1 µM in vitro) alleviated these alterations through NF-κB/MAPKs/NLRP3 signaling pathways but had no effect on pain hypersensitivity. TLR4 strongly interacted with RUS, and TLR4 overexpression abolished the effects of RUS on anxiety and neuroinflammation. RUS exerts anti-inflammatory and anxiolytic effects via TLR4-mediated NF-κB/MAPKs/NLRP3 signaling pathways, which provides a basis for the treatment of chronic pain-induced anxiety.

Mesoporous Metal Fluoride Nanocomposite Films with Tunable Optical Properties Derived from Precursor Instability.

The precisely tailored refractive index of optical materials is the key to utilizing and manipulating light during its propagation through the matrix, thereby improving their application performances. In this paper, mesoporous metal fluoride films with engineered composition (MgF2 :LaF3 ) are demonstrated to achieve finely tunable refractive indices. These films are prepared using a precursor-derived one-step assembly approach via the simple mixing of precursor solutions (Mg(CF3 OO)2 and La(CF3 OO)3 ); then pores are formed simultaneously during solidification owing to the inherent instability of La(CF3 OO)3 . The mesoporous structures are realized through Mg(CF3 OO)2 and La(CF3 OO)3 ions, which interacted with each other based on their electrostatic forces, providing a wide range of refractive indices (from 1.37 to 1.16 at 633 nm). Furthermore, it is systematically several MgF2(1-x) -LaF3(x) layers with different compositions (x = 0.0, 0.3, and 0.5) to form the graded refractive index coating that is optically consecutive between the substrate and the air for broadband and omnidirectional antireflection. An average transmittance of ≈98.03% (400-1100 nm) is achieved with a peak transmittance of ≈99.04% (at 571 nm), and the average antireflectivity is maintained at ≈15.75% even at an incidence of light of 65° (400-850 nm).

TGPS: dynamic point cloud down-sampling of the dense point clouds for Terracotta Warrior fragments.

The dense point clouds of Terracotta Warriors obtained by a 3D scanner have a lot of redundant data, which reduces the efficiency of the transmission and subsequent processing. Aiming at the problems that points generated by sampling methods cannot be learned through the network and are irrelevant to downstream tasks, an end-to-end specific task-driven and learnable down-sampling method named TGPS is proposed. First, the point-based Transformer unit is used to embed the features and the mapping function is used to extract the input point features to dynamically describe the global features. Then, the inner product of the global feature and each point feature is used to estimate the contribution of each point to the global feature. The contribution values are sorted by descending for different tasks, and the point features with high similarity to the global features are retained. To further learn rich local representation, combined with the graph convolution operation, the Dynamic Graph Attention Edge Convolution (DGA EConv) is proposed as a neighborhood graph for local feature aggregation. Finally, the networks for the downstream tasks of point cloud classification and reconstruction are presented. Experiments show that the method realizes the down-sampling under the guidance of the global features. The proposed TGPS-DGA-Net for point cloud classification has achieved the best accuracy on both the real-world Terracotta Warrior fragments and the public datasets.

Regulation of the pigment production by changing Cell morphology and gene expression of Monascus ruber in high-sugar synergistic high-salt stress fermentation.

AIMS: Extreme environment of microbial fermentation is the focus of research, which provides new thinking for the production and application of Monascus pigments (MPs). In this work, the high-sugar synergistic high-salt stress fermentation (HSSF) of MPs was investigated. METHODS AND RESULTS: The Monascus fungus grew well under HSSF conditions with 35 g L-1 NaCl and 150 g L-1 glucose, and the extracellular yellow pigment and intracellular orange pigment yield in HSSF was 98% and 43% higher than that in conventional fermentation, respectively. Moreover, the mycelial morphology was maintained in a better status with more branches and complete surface structure, indicating good biocatalytic activity for pigment synthesis. Four extracellular yellow pigments (Y1, Y2, Y3, and Y4) were transformed into each other, and ratio of the relative content of intracellular orange pigments to yellow pigments (O/Y) significantly (P < 0.05) changed. Moreover, the ratio of unsaturated fatty acids to saturated fatty acids (unsaturated/saturated) was significantly (P < 0.05) increased, indicating that the metabolism and secretion of intracellular and extracellular pigment might be regulated in HSSF. The pigment biosynthesis genes mppB, mppC, mppD, MpPKS5, and MpFasB2 were up-regulated, whereas the genes mppR1, mppR2, and mppE were down-regulated, suggesting that the gene expression to regulate pigment biosynthesis might be a dynamic change process in HSSF. CONCLUSIONS: The HSSF system of MPs is successfully performed to improve the pigment yields. Mycelial morphology is varied to enhanced pigment secretion, and gene expression is dynamically regulated to promote pigment accumulation in HSSF.

The Role of Oxytocin in Early-Life-Stress-Related Neuropsychiatric Disorders.

Early-life stress during critical periods of brain development can have long-term effects on physical and mental health. Oxytocin is a critical social regulator and anti-inflammatory hormone that modulates stress-related functions and social behaviors and alleviates diseases. Oxytocin-related neural systems show high plasticity in early postpartum and adolescent periods. Early-life stress can influence the oxytocin system long term by altering the expression and signaling of oxytocin receptors. Deficits in social behavior, emotional control, and stress responses may result, thus increasing the risk of anxiety, depression, and other stress-related neuropsychiatric diseases. Oxytocin is regarded as an important target for the treatment of stress-related neuropsychiatric disorders. Here, we describe the history of oxytocin and its role in neural circuits and related behaviors. We then review abnormalities in the oxytocin system in early-life stress and the functions of oxytocin in treating stress-related neuropsychiatric disorders.

An Active Bio-Based Food Packaging Material of ZnO@Plant Polyphenols/Cellulose/Polyvinyl Alcohol: DESIGN, Characterization and Application.

Active packaging materials protect food from deterioration and extend its shelf life. In the quest to design intriguing packaging materials, biocomposite ZnO/plant polyphenols/cellulose/polyvinyl alcohol (ZnPCP) was prepared via simple hydrothermal and casting methods. The structure and morphology of the composite were fully analyzed using XRD, FTIR, SEM and XPS. The ZnO particles, plant polyphenols (PPL) and cellulose were found to be dispersed in PVA. All of these components share their unique functions with the composite's properties. This study shows that PPL in the composite not only improves the ZnO dispersivity in PVA as a crosslinker, but also enhances the water barrier of PVA. The ZnO, PPL and cellulose work together, enabling the biocomposite to perform as a good food packaging material with only a 1% dosage of the three components in PVA. The light shielding investigation showed that ZnPCP-10 can block almost 100% of both UV and visible light. The antibacterial activities were evaluated by Gram-negative Escherichia coli (E. coli) and Gram-positive staphylococcus aureus (S. aureus), with 4.4 and 6.3 mm inhibition zones, respectively, being achieved by ZnPCP-10. The enhanced performance and easy degradation enables the biocomposite ZnPCP to be a prospect material in the packaging industry.

Structural Elucidation and Cytotoxic Activity of New Monoterpenoid Indoles from Gelsemium elegans.

Two new monoterpenoid indole alkaloids, gelselegandines F (1) and G (2), were isolated from the aerial parts of Gelsemium elegans. Their structures were elucidated by means of spectroscopic techniques and quantum chemical calculations. The ECD calculations were conducted at the B3LYP/6-311G(d,p) level and NMR calculations were carried out using the Gauge-Including Atomic Orbitals (GIAO) method. Structurally, the two new compounds possessed rare, cage-like, monoterpenoid indole skeletons. All isolated compounds and the total alkaloids extract were tested for cytotoxicity against four different tumor cell lines. The total alkaloids extract of G. elegans exhibited significant antitumor activity with IC50 values ranging from 32.63 to 82.24 ug/mL. In order to discover anticancer leads from the active extraction, both new indole compounds (1-2) were then screened for cytotoxicity. Interestingly, compound 2 showed moderate cytotoxicity against K562 leukemia cells with an IC50 value of 57.02 uM.

Novosphingobium percolationis sp. nov. and Novosphingobium huizhouense sp. nov., isolated from landfill leachate of a domestic waste treatment plant.

Two strains designated as c1T and c7T, were isolated from the landfill leachate of a domestic waste treatment plant in Huizhou City, Guangdong Province, PR China. The cells of both strains were aerobic, rod-shaped, non-motile and formed yellow colonies on Reasoner's 2A agar plates. Strain c1T grew at 10-42 °C (optimum, 30 °C), pH 4.5-10.5 (optimum, pH 7.0) and 0-2.0 % (w/v) NaCl (optimum, 0-0.5 %). Strain c7T grew at 10-42 °C (optimum, 30 °C), pH 4.5-10.5 (optimum, pH 6.0) and 0-2.0 % (w/v) NaCl (optimum, 0-0.5 %). Phylogenetic analyses revealed that strains c1T and c7T belong to the genus Novosphingobium. The 16S rRNA gene sequence similarities of strains c1T and c7T to the type strains of Novosphingobium species were 94.5-98.2 % and 94.3-99.1 %, respectively. The calculated pairwise average nucleotide identity values among strains c1T, c7T and the reference strains were in the range of 75.2-85.9 % and the calculated pairwise average amino acid identity values among strains c1T, c7T and reference strains were in the range of 72.0-88.3 %. Their major respiratory quinone was Q-10, and the major cellular fatty acids were C18 : 1 ω7c, C18 : 0, C16 : 1 ω7c, C16 : 0 and C14 : 0 2OH. The major polar lipids of strains c1T and c7T were phosphatidylethanolamine, diphosphatidylglycerol, phosphatidylglycerol, sphingoglycolipid, unidentified lipids and unidentified phospholipid. Based on phenotypic, chemotaxonomic, phylogenetic and genomic results from this study, strains c1T and c7T should represent two independent novel species of Novosphingobium, for which the names Novosphingobium percolationis sp. nov. (type strain c1T=GDMCC 1.2555T=KCTC 82826T) and Novosphingobium huizhouense sp. nov. (type strain c7T=GDMCC 1.2556T=KCTC 82827T) are proposed. The gene function annotation results of strains c1T and c7T suggest that they could play an important role in the degradation of organic pollutants.

Pharmacodynamic, pharmacokinetic, and phase 1a study of bisthianostat, a novel histone deacetylase inhibitor, for the treatment of relapsed or refractory multiple myeloma.

HDAC inhibitors (HDACis) have been intensively studied for their roles and potential as drug targets in T-cell lymphomas and other hematologic malignancies. Bisthianostat is a novel bisthiazole-based pan-HDACi evolved from natural HDACi largazole. Here, we report the preclinical study of bisthianostat alone and in combination with bortezomib in the treatment of multiple myeloma (MM), as well as preliminary first-in-human findings from an ongoing phase 1a study. Bisthianostat dose dependently induced acetylation of tubulin and H3 and increased PARP cleavage and apoptosis in RPMI-8226 cells. In RPMI-8226 and MM.1S cell xenograft mouse models, oral administration of bisthianostat (50, 75, 100 mg·kg-1·d-1, bid) for 18 days dose dependently inhibited tumor growth. Furthermore, bisthianostat in combination with bortezomib displayed synergistic antitumor effect against RPMI-8226 and MM.1S cell in vitro and in vivo. Preclinical pharmacokinetic study showed bisthianostat was quickly absorbed with moderate oral bioavailability (F% = 16.9%-35.5%). Bisthianostat tended to distribute in blood with Vss value of 0.31 L/kg. This distribution parameter might be beneficial to treat hematologic neoplasms such as MM with few side effects. In an ongoing phase 1a study, bisthianostat treatment was well tolerated and no grade 3/4 nonhematological adverse events (AEs) had occurred together with good pharmacokinetics profiles in eight patients with relapsed or refractory MM (R/R MM). The overall single-agent efficacy was modest, stable disease (SD) was identified in four (50%) patients at the end of first dosing cycle (day 28). These preliminary in-patient results suggest that bisthianostat is a promising HDACi drug with a comparable safety window in R/R MM, supporting for its further phase 1b clinical trial in combination with traditional MM therapies.

UMA-Net: an unsupervised representation learning network for 3D point cloud classification.

The success of deep neural networks usually relies on massive amounts of manually labeled data, which is both expensive and difficult to obtain in many real-world datasets. In this paper, a novel unsupervised representation learning network, UMA-Net, is proposed for the downstream 3D object classification. First, the multi-scale shell-based encoder is proposed, which is able to extract the local features from different scales in a simple yet effective manner. Second, an improved angular loss is presented to get a good metric for measuring the similarity between local features and global representations. Subsequently, the self-reconstruction loss is introduced to ensure the global representations do not deviate from the input data. Additionally, the output point clouds are generated by the proposed cross-dim-based decoder. Finally, a linear classifier is trained using the global representations obtained from the pre-trained model. Furthermore, the performance of this model is evaluated on ModelNet40 and applied to the real-world 3D Terracotta Warriors fragments dataset. Experimental results demonstrate that our model achieves comparable performance and narrows the gap between unsupervised and supervised learning approaches in downstream object classification tasks. Moreover, it is the first attempt to apply the unsupervised representation learning for 3D Terracotta Warriors fragments. We hope this success can provide a new avenue for the virtual protection of cultural relics.

ULD-Net: 3D unsupervised learning by dense similarity learning with equivariant-crop.

Although many recent deep learning methods have achieved good performance in point cloud analysis, most of them are built upon the heavy cost of manual labeling. Unsupervised representation learning methods have attracted increasing attention due to their high label efficiency. How to learn more useful representations from unlabeled 3D point clouds is still a challenging problem. Addressing this problem, we propose a novel unsupervised learning approach for point cloud analysis, named ULD-Net, consisting of an equivariant-crop (equiv-crop) module to achieve dense similarity learning. We propose dense similarity learning that maximizes consistency across two randomly transformed global-local views at both the instance level and the point level. To build feature correspondence between global and local views, an equiv-crop is proposed to transform features from the global scope to the local scope. Unlike previous methods that require complicated designs, such as negative pairs and momentum encoders, our ULD-Net benefits from the simple Siamese network that relies solely on stop-gradient operation preventing the network from collapsing. We also utilize the feature separability constraint for more representative embeddings. Experimental results show that our ULD-Net achieves the best results of context-based unsupervised methods and comparable performances to supervised models in shape classification and segmentation tasks. On the linear support vector machine classification benchmark, our ULD-Net surpasses the best context-based method spatiotemporal self-supervised representation learning (STRL) by 1.1% overall accuracy. On tasks with fine-tuning, our ULD-Net outperforms STRL under fully supervised and semisupervised settings, in particular, 0.1% accuracy gain on the ModelNet40 classification benchmark, and 0.6% medium intersection of union gain on the ShapeNet part segmentation benchmark.

Tanshinone IIA improves contextual fear- and anxiety-like behaviors in mice via the CREB/BDNF/TrkB signaling pathway.

Posttraumatic stress disorder (PTSD) is one of the most common psychiatric diseases, which is characterized by the typical symptoms such as re-experience, avoidance, and hyperarousal. However, there are few drugs for PTSD treatment. In this study, conditioned fear and single-prolonged stress were employed to establish PTSD mouse model, and we investigated the effects of Tanshinone IIA (TanIIA), a natural product isolated from traditional Chinese herbal Salvia miltiorrhiza, as well as the underlying mechanisms in mice. The results showed that the double stress exposure induced obvious PTSD-like symptoms, and TanIIA administration significantly decreased freezing time in contextual fear test and relieved anxiety-like behavior in open field and elevated plus maze tests. Moreover, TanIIA increased the spine density and upregulated synaptic plasticity-related proteins as well as activated CREB/BDNF/TrkB signaling pathway in the hippocampus. Blockage of CREB remarkably abolished the effects of TanIIA in PTSD model mice and reversed the upregulations of p-CREB, BDNF, TrkB, and synaptic plasticity-related protein induced by TanIIA. The molecular docking simulation indicated that TanIIA could interact with the CREB-binding protein. These findings indicate that TanIIA ameliorates PTSD-like behaviors in mice by activating the CREB/BDNF/TrkB pathway, which provides a basis for PTSD treatment.

Biological Activities and Secondary Metabolites from Sophora tonkinensis and Its Endophytic Fungi.

The roots of Sophora tonkinensis Gagnep., a traditional Chinese medicine, is known as Shan Dou Gen in the Miao ethnopharmacy. A large number of previous studies have suggested the usage of S. tonkinensis in the folk treatment of lung, stomach, and throat diseases, and the roots of S. tonkinensis have been produced as Chinese patent medicines to treat related diseases. Existing phytochemical works reported more than 300 compounds from different parts and the endophytic fungi of S. tonkinensis. Some of the isolated extracts and monomer compounds from S. tonkinensis have been proved to exhibit diverse biological activities, including anti-tumor, anti-inflammatory, antibacterial, antiviral, and so on. The research progress on the phytochemistry and pharmacological activities of S. tonkinensis have been systematically summarized, which may be useful for its further research.

Machine learning with neuroimaging data to identify autism spectrum disorder: a systematic review and meta-analysis.

PURPOSE: Autism Spectrum Disorder (ASD) is diagnosed through observation or interview assessments, which is time-consuming, subjective, and with questionable validity and reliability. Thus, we aimed to evaluate the role of machine learning (ML) with neuroimaging data to provide a reliable classification of ASD. METHODS: A systematic search of PubMed, Scopus, and Embase was conducted to identify relevant publications. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to assess the studies' quality. A bivariate random-effects model meta-analysis was employed to evaluate the pooled sensitivity, the pooled specificity, and the diagnostic performance through the hierarchical summary receiver operating characteristic (HSROC) curve of ML with neuroimaging data in classifying ASD. Meta-regression was also performed. RESULTS: Forty-four studies (5697 ASD and 6013 typically developing individuals [TD] in total) were included in the quantitative analysis. The pooled sensitivity for differentiating ASD from TD individuals was 86.25 95% confidence interval [CI] (81.24, 90.08), while the pooled specificity was 83.31 95% CI (78.12, 87.48) with a combined area under the HSROC (AUC) of 0.889. Higgins I2 (> 90%) and Cochran's Q (p < 0.0001) suggest a high degree of heterogeneity. In the bivariate model meta-regression, a higher pooled specificity was observed in studies not using a brain atlas (90.91 95% CI [80.67, 96.00], p = 0.032). In addition, a greater pooled sensitivity was seen in studies recruiting both males and females (89.04 95% CI [83.84, 92.72], p = 0.021), and combining imaging modalities (94.12 95% [85.43, 97.76], p = 0.036). CONCLUSION: ML with neuroimaging data is an exciting prospect in detecting individuals with ASD but further studies are required to improve its reliability for usage in clinical practice.

Performance evaluation of immunoassay for infectious diseases on the Alinity i system.

BACKGROUND: Although a diagnosis of infectious diseases is essential for timely treatment, the performance of diagnostic tests has been hardly evaluated due to variable results that are influenced by multiple factors in different conditions. In the present study, the performance of the Alinity i system, which is a newly developed immunoassay to diagnose infectious diseases, was evaluated. METHODS: We evaluated the precision, linearity, correlation, and carryover of 16 analytes (HAV Ab IgG, HBsAg, HBeAg, anti-HBc, anti-HBe, anti-HBs, anti-HCV, HIV Ag/Ab, EBV VCA IgM, EBV VCA IgG, EBV EBNA IgG, CMV IgM, CMV IgG, Toxoplasma IgG, Rubella IgG, and Syphilis TP) of Alinity i by comparison with ARCHITECT i2000SR system following the rationale of the Clinical and Laboratory Standards Institute (CLSI). RESULTS: For quantitative tests, the coefficients of variation (CV) % of repeatability and intermediate precision were between 0% and 4.18%. The coefficients of the linearity (r2 ) over a widely tested analytical range were ≥ 0.990 and the correlation between Alinity i and the ARCHITECT i2000SR system was strong (r ≥ 0.994). For qualitative tests, the agreement between Alinity i and the ARCHITECT i2000SR system was excellent (kappa coefficient 1) with 100% sensitivity and specificity. Carryover rates for all analytes were less than 1.0% (-0.11% ~ 0.21%). CONCLUSION: The Alinity i system showed good analytical performance and favorable comparability with the ARCHITECT i2000SR. It could be suitable as a routine immunoassay analyzer for screening and diagnosis of infectious disease.

Optogenetic manipulation of astrocytes from synapses to neuronal networks: A potential therapeutic strategy for neurodegenerative diseases.

Astrocytes are the most widespread and heterogeneous glial cells in the central nervous system and key regulators for brain development. They are capable of receiving neurotransmitters produced by synaptic activities and regulating synaptic functions by releasing gliotransmitters as part of the tripartite synapse. In addition to communicating with neurons at synaptic levels, astrocytes can integrate into inhibitory neural networks to interact with neurons in neuronal circuits. Astrocytes are closely related to the pathogenesis and pathological processes of neurodegenerative diseases (NDs). Recently, optogenetics has now been applied to reveal the function of astrocytes in physiology and pathology. Herein, we discuss the possibility whether optogenetics could be used to control the release of gliotransmitters and regulate astrocytic membrane channels. Thus, the capability of modulating the bidirectional interactions between astrocytes and neurons in both synaptic and neuronal networks via optogenetics is evaluated. Furthermore, we discuss that manipulating astrocytes via optogenetics might be an effective way to investigate the potential therapeutic strategy for NDs.

Dynamics of a nutrient-phytoplankton model with random phytoplankton mortality.

This study formulates a stochastic nutrient-phytoplankton model which incorporates the effect of white noise on phytoplankton growth. The global existence and uniqueness of a positive solution, stochastic boundedness, and stochastically asymptotic stability are well explored. A stochastic ecological reproductive index R0s is formulated to characterize the global dynamics. The theoretical analysis demonstrates that, if R0s<1, then phytoplankton dies out with probability one; if R0s>1 and some other conditions hold, then there exists an invariant and asymptotically stable density of the system and the approach involves integral Markov semigroups theory. Numerical simulations are presented to illustrate the analytical findings and to investigate the long-time effect of water temperature, light, nutrients, and environmental noise on the dynamic evolution of phytoplankton.